Includes Security, SRM, Cloud, ICM, SaaS, Business Intelligence, Data Warehouse, Database Appliances, NFM, Storage Management.
This section covers all forms of technologies that impact IT infrastructure management. Taneja Group analysts particularly focus on the interplay between server virtualization and storage, with and without virtualization, and study the impact on performance, security and management of the IT infrastructure. This section also includes all aspects of storage management (SRM, SMI-S) and the role of cross correlation engines on overall performance of an application. Storage virtualization technologies (In-band, Out-of-band, split path architectures or SPAID) are all covered in detail. Data Security, whether for data in-flight or at-rest and enterprise level key management issues are covered along with all the players that make up the ecosystems.
As databases continue to grow larger and more complex they present issues in terms of security, performance and management. Taneja Group analysts cover the vendors and the technologies that harness the power of archiving to reduce the size of active databases. We also cover specialized database appliances that have become the vogue lately. All data protection issues surrounding databases are also covered in detail. We write extensively on this topic for the benefit of the IT user.
Myths prevail in the IT industry just as they do in every other facet of life. One common myth is that mid-sized workloads, exemplified by smaller versions of mission critical applications, are only to be found in mid-size companies. The reality is mid-sized workloads exist in businesses of all sizes. Another common fallacy is that small and mid-size enterprises (SMEs) or departments within large organizations and Remote/Branch Offices (ROBOs) have lesser storage requirements than their larger enterprise counterparts. The reality is companies and groups of every size have business-critical applications and these workloads require enterprise-grade storage solutions that offer high-performance, reliability and strong security. The only difference is IT groups managing mid-sized workloads frequently have significant budget constraints. This is a tough combination and presents a big challenge for storage vendors striving to satisfy mid-sized workload needs.
A recent survey conducted by Taneja Group showed mid-size and enterprise needs for high-performance storage were best met by highly virtualized systems that minimize disruption to their current environment. Storage virtualization is key because it abstracts away all the differences of various storage boxes to create 1) a single virtualized storage pool 2) a common set of data services and 3) a common interface to manage storage resources. These storage virtualization capabilities are beneficial to the overall enterprise storage market and they are especially attractive to mid-sized storage customers because storage virtualization is the core underlying capability that drives efficiency and affordability.
The combination of affordability, manageability and enterprise-grade functionality is the core strength of the IBM Storwize family built upon IBM Spectrum Virtualize, the quintessential virtualization software that has been hardened for over a decade with IBM SAN Volume Controller (SVC). Simply stated – few enterprise storage solutions match IBM Storwize’s ability to deliver enterprise-grade functionality at such a low cost. From storage virtualization and auto-tiering to real-time data compression and proven reliability, Storwize with Spectrum Virtualize offers an end-to-end storage footprint and centralized management that delivers highly efficient storage for mid-sized workloads, regardless of whether they exist in small or large companies.
In this paper, we will look at the key requirements for mid-sized storage and we will evaluate IBM Storwize with Spectrum Virtualize’s ability to tackle mid-sized workload requirements. We will also present an overview of IBM Storwize family and provide a comparison of the various models in the Storwize portfolio.
Virtual Instruments, the company created by the combination of the original Virtual Instruments and Load DynamiX, recently made available a free cloud-based service and community called WorkloadCentral. The service is designed to help storage professionals understand workload behavior and improve their knowledge of storage performance. Most will find valuable insights into storage performance with the simple use of this free service. For those who want to get a deeper understanding of workload behavior over time, or evaluate different storage products to determine which one is right for their specific application environment, or optimize their storage configurations for maximum efficiency, they can buy additional Load DynamiX Enterprise products available from the company.
The intent with WorkloadCentral is to create a web-based community that can share information about a variety of application workloads, perform workload analysis and create workload simulations. In an industry where workload sharing has been almost absent, this service will be well received by storage developers and IT users alike.
Read on to understand where WorkloadCentral fits into the overall application and storage performance spectrum...
This Field Report was created by Taneja Group for Nutanix in late 2014 with updates in 2015. The Taneja Group analyzed the experiences of seven Nutanix Xtreme Computing Platform customers and seven Virtual Computing Environment (VCE) Vblock customers. We did not ‘cherry-pick’ customers for dissatisfaction, delight, or specific use case; we were interested in typical customers’ honest reactions.
As we talked in detail to these customers, we kept seeing the same patterns: 1) VCE users were interested in converged systems; and 2) they chose VCE because VCE partners Cisco, EMC, and/or VMware were embedded in their IT relationships and sales. The VCE process had the advantage of vendor familiarity, but it came at a price: high capital expense, infrastructure and management complexity, expensive support contracts, and concerns over the long-term viability of the VCE partnership (see an opinion of the DELL/EMC merger at end of this document). VCE customers typically did not research other options for converged infrastructure prior to deploying the VCE Vblock solution.
In contrast, Nutanix users researched several convergence and hyperconvergence vendors to determine the best possible fit. Nutanix’ advanced web-scale framework gave them simplified architecture and management, reasonable acquisition and operating costs, and considerably faster time to value.
Our conclusion, based on the amount of time and effort spent by the teams responsible for managing converged infrastructure, is that VCE Vblock deployments represent an improvement over traditional architectures, but Nutanix hyperconvergence – especially with its web-scale architecture – is an big improvement over VCE.
This Field Report will compare customer experiences with Nutanix hyperconverged, web-scale infrastructure to VCE Vblock in real-world environments.
Hyperconvergence is one of the hottest IT trends going in to 2016. In a recent Taneja Group survey of senior enterprise IT folks we found that over 25% of organizations are looking to adopt hyperconvergence as their primary data center architecture. Yet the centralized enterprise datacenter may just be the tip of the iceberg when it comes to the vast opportunity for hyperconverged solutions. Where there are remote or branch office (ROBO) requirements demanding localized computing, some form of hyperconvergence would seem the ideal way to address the scale, distribution, protection and remote management challenges involved in putting IT infrastructure “out there” remotely and in large numbers.
However, most of today’s popular hyperconverged appliances were designed as data center infrastructure, converging data center IT resources like servers, storage, virtualization and networking into Lego™ like IT building blocks. While these at first might seem ideal for ROBOs – the promise of dropping in “whole” modular appliances precludes any number of onsite integration and maintenance challenges, ROBOs have different and often more challenging requirements than a datacenter. A ROBO does not often come with trained IT staff or a protected datacenter environment. They are, by definition, located remotely across relatively unreliable networks. And they fan out to the thousands (or tens of thousands) of locations.
Certainly any amount of convergence simplifies infrastructure making easier to deploy and maintain. But in general popular hyperconvergence appliances haven’t been designed to be remotely managed en masse, don’t address unreliable networks, and converge storage locally and directly within themselves. Persisting data in the ROBO is a recipe leading to a myriad of ROBO data protection issues. In ROBO scenarios, the datacenter form of hyperconvergence is not significantly better than simple converged infrastructure (e.g. pre-configured rack or blades in a box).
Riverbed’s SteelFusion we feel has brought full hyperconvergence benefits to the ROBO edge of the organization. They’ve married their world-class WANO technologies, virtualization, and remote storage “projection” to create what we might call “Edge Hyperconvergence”. We see the edge hyperconverged SteelFusion as purposely designed for companies with any number of ROBO’s that each require local IT processing.
Virtualization has matured and become widely adopted in the enterprise market. HyperConverged Infrastructure (HCI), with virtualization at its core, is taking the market by storm, enabling virtualization for businesses of all sizes. The success of these technologies has been driven by an insatiable desire to make IT simpler, faster, and more efficient. IT can no longer afford the time and effort required to create custom infrastructure from best-of-breed DIY components.
With HCI, the traditional three-tier architecture has been collapsed into a single system that is purpose-built for virtualization. In these solutions, the hypervisor, compute, storage, and advanced data services are integrated into an x86 industry-standard building block. The immense success of this approach has led to increased competition in this space and the customers are required to sort through the various offerings, analyzing key attributes to determine which are significant.
One of these competing vendors, Pivot3, was founded in 2002 and has been in the HCI market since 2008, well before the term HyperConverged was used. For many years, Pivot3’s vSTAC architecture has provided the most efficient scale-out Software-Defined Storage (SDS) system available on the market. This efficiency is attributed to three design innovations. The first is their extremely efficient and reliable erasure coding technology called Scalar Erasure Coding. Conversely, many leading HCI implementations use replication-based redundancy techniques which are heavy on storage capacity utilization. Scalar Erasure Coding from Pivot3 can deliver significant capacity savings depending on the level of drive protection selected. The second innovation is Pivot3’s Global Hyperconvergence which creates a cross-cluster virtual SAN, the HyperSAN: in case of appliance failure, a VM migrates to another node and continues operations without the need to divert compute power to copy data over to that node. The third innovation has been a reduction in CPU overhead needed to implement the SDS features and other VM centric management tasks. Implementation of the HCI software uses the same CPU complex as business applications, this additional usage is referred to as the HCI overhead tax. HCI overhead tax is important since the licensing cost for many applications and infrastructure software are based on a per CPU basis. Even with today’s ever- increasing cores per CPU there still can be significant cost saving by keeping the HCI overhead tax low.
The Pivot3 family of HCI products delivering high data efficiency with a very low overhead are an ideal solution for storage-centric business workload environments where storage costs and reliability are critical success factors. One example of this is a VDI implementation where cost per seat determines success. Other examples would be capacity-centric workloads such as big data or video surveillance that could benefit from a Pivot3 HCI approach with leading storage capacity and reliability. In this paper we compare Pivot3 with other leading HCI architectures. We utilized data extracted from the alternative HCI vendor’s reference architectures for VDI implementations. Using real world examples, we have demonstrated that with other solutions, users must purchase up to 136% more raw storage capacity and up to 59% more total CPU cores than are required when using equivalent Pivot3 products. These impressive results can lead to significant costs savings.
Decades of constantly advancing computing solutions have changed the world in tremendous ways, but interestingly, the IT folks running the show have long been stuck with only piecemeal solutions for managing and optimizing all that blazing computing power. Sometimes it seems like IT is a pit crew servicing a modern racing car with nothing but axes and hammers – highly skilled but hampered by their legacy tools.
While that may be a slight exaggeration, there is a serious lack of interoperability or opportunity to create joint insight between the highly varied perspectives that individual IT tools produce (even if each is useful in its own purpose). There simply has never been a widely adopted standard for creating, storing or sharing system management data, much less a cross-vendor way to holistically merge heterogeneously collected or produced management data together – even for the beneficial use of harried and often frustrated IT owners that might own dozens or more differently sourced system management solutions. That is until now.
OpsDataStore has brought the IT management game to a new level with an easy to deploy, centralized, intelligent – and big data enabled – management data “service”. It readily sucks in all the lowest level, fastest streaming management data from a plethora of tools (several ready to go at GA, but easily extended to any data source), automatically and intelligently relates data from disparate sources into a single unified “agile” model, directly provides fundamental visualization and analysis, and then can serve that unified and related data back out to enlightened and newly comprehensive downstream management workflows. OpsDataStore drops in and serves as the new systems management “nexus” between formerly disparate vendor and domain management solutions.
If you have ever been in IT, you’ve no doubt written scripts, fiddled with logfiles, created massive spreadsheets, or otherwise attempted to stitch together some larger coherent picture by marrying and merging data from two (or 18) different management data sources. The more sources you might have, the more the problem (or opportunity) grows non-linearly. OpsDataStore promises to completely fill in this gap, enabling IT to automatically multiply the value of their existing management solutions.